COMMUNITY UPDATE

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Having a robot for a co-worker may not be such a far-fetched idea. “The really interesting thing is how fast the development of cobots has been,” says Mark Parsons, Chief Customer Officer for the UK&I at DHL Supply Chain. “If we go back two years, a cobot offered about half the productivity of a human. Today the technology is twice as productive.”

At DHL, Mark says that cobots are used on the packing production line. “If bottles of shampoo are being packed, a cobot is able to recognise if anything other than shampoo makes it onto the line and then remove it. Two years ago, a cobot would have packed whatever came down the line – that is how quickly this technology is moving.”

He says that what has specifically changed is the number of sensors that can now be fixed to these machines, enabling them to complete a far broader range of tasks with greater accuracy. “Cobots are easy to work with because they can be taught to complete simple tasks; you can quickly manipulate them to do the job you want them to do,” he says.

According to Camilla Perselli, Relationship Manager at Criticaleye, “advances in robotics and automation are set to transform the working environment across multiple sectors, provided proper thought and planning is given to how this technology is implemented”.

She notes that organisations will not succeed if they take a siloed approach. “Allowing the tech side of your business to run autonomously may help to deliver a quick tech win in the short term, but when you come to scale up the solution across the company you will soon run into problems,” she says.

Expanding on this point, Adam Green, Chief Risk Officer at Equiniti, says: “Robots and artificially intelligent systems need data and, in order to provide that, you have to build an environment where everything that matters is being digitised.”

Adam argues that it is absolutely critical to understand what tasks robots are good at and what data they require: “The more you constrain the problem, the more efficiently the computer will ‘solve’ the problem, so if you are doing image recognition, for example, or looking for cancer cells, it’s a very constrained problem and therefore the computer will outperform humans.

“But, if you are looking through a messy environment, where lots of things can happen, lots of unconstrained, unexpected events, the computer is likely to perform erratically and offer poor ‘solutions’. If you can define a problem well and identify its composite parts, computers will be very good at automating that stage of a process.”

Not So Human Resources

This technology will require a different approach to how CEOs and senior executives think about talent and workforce capability. Simon Bartlett, Managing Consultant at OEE Consulting, says: “New management skills are going to need to be developed in order to manage successfully both robots and people. Managers will have to learn to understand the limitations of a robot team. This requires forecasting, planning, allocating work, ensuring that the robot has enough work to be productive alongside human users.

"As we automate the simple work, what remains is the difficult work. It is almost inevitable that in the future businesses are going to need fewer people who are better skilled."

The challenge a lot of companies face, when looking at how this technology can solve problems or make a business move faster, is to create better cross-team collaboration. Adam says: "Typically, companies can be very good at process, process efficiency and process optimisation. This has conditioned people to look at things in a particular way.

“The way forward is to have a number of people with a broader outlook, who consider everybody’s views. Without multiple opinions being brought to the table, it’s often very difficult for teams to effectively imagine new ways to solve a problem.”

Mark warns that patience is also required. “There is always a sense of over-ambition when it comes to adopting new technology; there tends to be a belief that a business will jump forward by light years overnight.

“The truth is that, although new tech has the potential to deliver change in the long run, it will not start to do so on day one. Most companies have a very high expectation that the return on investment will come much quicker than the technology is realistically able to deliver.”